Coronary heart disease (CHD) and cerebrovascular disease result from platelet thrombus formation at the site of a ruptured atherosclerotic plaque. Numerous studies have shown enhanced platelet reactivity, and increased platelet count and volume are risk factors for CHD events and fatality, and a recent NHLBI Working Group concluded that variation in platelet reactivity is a major determinant of ischemic events, like MI or stroke. Genome wide association studies (GWASs) have identified numerous common genetic variants associated with the risk of CHD and platelet function parameters, but most of the positive hits are not causative of the phenotype. To understand the cellular mechanisms by which these variants affect platelet function it is imperative to know the repertoire of mRNAs, miRNAs and lncRNAs expressed in the cell of interest. Our team has been a leader in the field of platelet transcriptomics as well as functional assessment of variants in platelet genes. We have profiled mRNAs and miRNAs from 183 subjects using multiple platforms and have also performed platelet RNA-seq on 14 different subjects. This information provides a critical ability to filter, prioritize and obtain variant functional insights for evaluating GWAS SNPs associated with MI, stroke and platelet parameters. We have identified 142 mRNAs and 9 miRNAs that are expressed in platelets and linked to these GWAS hits. The goals of this proposal are to identify, assay, and validate functional variation previously tagged in GWASs of platelet-mediated ischemic arterial disease and of platelet phenotypes. Aim 1 will identify GWAS-linked mRNAs, miRNAs and lncRNAs that are functional in platelets. Candidate RNAs will be refined by association with platelet function, eQTLs and QTLs using our previously generated platelet RNA data. We will develop a supervised machine-learning, statistical pattern matching algorithm to prioritize likely platelet-functional genes. Gene-level assays in which we knock down mRNA, miRNA and lncRNA in our human megakaryocyte culture system, followed by assays for integrin activation and quantification of platelet number and volume will be used to confirm platelet functionality. Aim 2 will identify functionally divergent SNPs and haplotypes. We will impute missing SNPs and perform fine-mapping to the phenotypes of interest. Variants will be prioritized by association strength, annotation data, and predicted function using publically available resources and our own platelet eQTL data. Non-coding candidates will be tested by reporter gene assay and non-synonymous variants will be tested using functional assays in cell lines in which the endogenous gene has been silenced. We will validate our findings with a replication analysis in which we use an independent cohort dataset to quantify the association of the tested variants with the original GWAS phenotype.